Commonalities in stream connectivity restoration alternatives: an attempt to simplify barrier removal optimization

Movement within stream corridors is a basic life history requirement of many aquatic organisms. Barrier removal in streams has become a common practice in the United States aimed to restore organism dispersal and meet conservation objectives; however, there are social and economic costs to the removal of barriers. Accordingly, tools to prioritize barrier removal, particularly optimization techniques, can be used to evaluate cost‐benefit trade‐offs. Many of these techniques, however, require programming experience and are not available to natural resource managers. Furthermore, conservation objectives vary considerably depending on the life histories of organisms under consideration, and these opposing objectives, in conjunction with variant socioeconomic costs, will influence optimization solutions, specifically which barriers to remove. To promote the use of optimization tools, straightforward and open‐access platforms are needed to support use by managers, while also providing general approaches for holistic basin‐scale connectivity restoration. Herein, we use two case studies, White Oak Creek (small watershed) and the Roanoke River Basin (large basin), to explore the divergent outcomes stemming from different conservation objectives and socioeconomic costs used to prioritize barrier removal. We conducted optimization modeling using a widely accessible platform along with an open‐access solver plug‐in to support a wide variety of conservation objectives. We used simple approaches to find commonalities in barriers identified for removal among divergent conservation objectives and provide alternative (i.e., hybrid removal‐passage) strategies for approaching habitat restoration for diverse aquatic communities while increasing social benefits (i.e., hydropower energy). As expected, different conservation objectives aimed to support varied species life histories (e.g., diadromy, large‐river vs. small‐river potamodromy) have very different effects on optimization solutions. In both case studies, however, commonalities in solutions were identified through clustering groups of barriers into general connectivity restoration strategies. Furthermore, strategy types for a given barrier could be predicted with ≥72% accuracy using only four metrics. This suggests that optimization results can be simplified into general standards to support adoption of sustainable basin connectivity criteria strategies. Our framework provides a flexible and open‐access approach to conduct relatively complex optimization modeling for stream barrier prioritization, while examining potential for agreement among divergence conservation objectives.